Enhancing the Durability Properties of Soft Clay Using Nano-Modified Cementitious Additives
Bibliographic record
Abstract
This study focuses on studying the effect of nano-modified cementitious binders on soft clay soil, which is the most common type of soil in Winnipeg, Manitoba, Canada.The properties assessed were the unconfined compressive strength and durability of freezing-thawing and wetting-drying conditions.The soft clay was mixed with cement and slag; both were added at a dosage of 0 to 20% of the dried soil weight.Also, a nano-silica sol was added at a dosage of 0 to 2.4% of the dried soil weight (0 to 6% of the binder content).The unconfined compressive strength tests were done at 56 days of curing to allow for the latent hydraulic binder (slag) reactivity.Also, the freezing-thawing and wetting-drying characteristics started at 56 days of curing.In comparison to the mixtures containing slag and cement only, incorporating nano-silica in the cementitious system notably improved the properties of the treated mixtures, in terms of compressive strength, freezing-thawing durability factor, and wetting-drying durability factor.In particular, the ternary mix, compressing cement, slag, and nano-silica, has the potential to serve as an effective stabilizer for soft clay.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".